Star Category Research Articles

Menguak Strategi Manajemen Talenta Hotel Berbintang di Bali

Business competition in this globalization and digital era is very tight. General Managers & Human Resources Leaders face their own challenges. To work around this, qualified and highly qualified Human Resources are needed to be able to give the best contribution to the company, especially to respond to competition that arises in the business, especially related to the availability of talented employees. This study aims to obtain information about the implementation of Talent Management that has been carried out by star hotels in Bali. This research is exploratory research with a qualitative approach. The total number of respondents was 16 people consisting of 3 people from Prime Plaza Hotel & Suites Sanur-Bali, 4 people from Capella Ubud, 3 people from Swan Paradise a Pramana Experience, 3 people from Four Seasons Resort Bali, and 3 people from Mercure. Bali Legion. Where the selection of respondents represents a variety of hotel management, including hotels managed internationally (international chained hotels) and nationally (national chained hotels), 4 and 5 star categories. The application of Talent Management in hotels has a significant impact on producing competent and qualified Human Resources to support the increase in the company's competitiveness against its competitors. Another positive result is that the level of loyalty from employees to the company also increases. As was the case with the Capella Ubud Hotel, where their employees decided to resign because of a promotion, a better offer to cruise ship management, or abroad. The results obtained are that Talent Management is very important to do, because this system is effective and efficient in increasing employee competence, which will then increase the company's competitiveness against its competitors. Likewise with the Four Seasons Resort Bali, after the pandemic, many young people joined, and they joined the Four Seasons to see opportunities abroad. There have been quite a lot of employee transfers to overseas branches.

Causality between Service Quality and Customers’ Satisfaction Across Star Hotels

Background: To win the race of hares, one has to become a leopard performing in faster and pro-active manners than others to win the competition. But to come first and remain ahead of others for longer durations, demands quality initiatives in business processes and therefore the topic on quality in service operations beards paramount importance. Objectives: On this note, we have tried to assess the prevailing service quality of various star category hotels in the state of Odisha in India where the renowned SERVQUAL scale is employed to map the difference of opinions between the guests visiting the hotels. Materials & Methods: A total of 395 numbers of interviews were conducted through convenient sampling process and the data was captured through the use of a structured questionnaire. The collected data were assessed through the use of descriptive statistics that includes percentage calculations, cross tabulations, t-test, analysis of variance, correlation coefficient, and multiple regression analysis, etc. Results: The results revealed sorry state of affairs at the selected hotels where positive gap scores were obtained between the expectations and perceptions of the customers. Based upon the findings, curtain corrective measures are proposed in the study for enhancing the qualitative parameters of the hotels. Epilogue: Survival of the fittest is the word that describes the market scenario. The entities that remain fit, agile, anticipatory, proactive, caring, and most importantly quality conscious can only win the race with flying colours. Originality: This study analyzes the quality of various services initiatives prevailing at the star hotels in the state of Odisha in India for which our study can certainly help in generating different guidelines to ensure the optimal levels of quality as desired by the guests at the hotels which will help in development of a long term and sustainable quality initiative in the sector compared to international standards.

Gender Equality: An Exploratory Study of Practices Adopted by Star Hotels

Gender equality can be understood as equal access to opportunities and resources regardless of the gender. An awareness of the gender inequality has prompted the hotel industry to review their policies and practices. This research studies gender equality practices adopted by the human resource department of the star category hotels to overcome the above challenges and give equal opportunities as well as support towards the work equilibrium. The results indicate that the practices adopted by the hotels are inclined towards gender equality, especially women centric. It was observed that women employees have taken up positions at all levels in hotels owing to the changing trends in the policies and practices. The results suggest that certain departments like housekeeping and front offices are dominated by women employees, whereas the food production department has male employees. The research is confined to and emphasizes on gender equality with respect to the hotel industry.

Determining Competitiveness of Indonesian Export Commodities using Revealed Comparative Analysis

This article aims to analyze Indonesian products’ competitiveness in the global market using the static revealed comparative advantage (SRCA) and the dynamic revealed comparative advantage (DRCA). DRCA is considered superior to RCA because it takes into account the time element. The current research combines DRCA and RCA to provide an analytical comparison. The data were collected from the International Trade Centre, classified according to the Harmonized System (HS) from 2013 to 2019. Using SRCA, Indonesia’s tin and articles’ competitiveness only contributes 0.95% of Indonesia's total exports. The most significant shares of exports are mineral fuels, mineral oils, and their distillation products; bituminous substances; animal or vegetable fats and oils, and their cleavage products; and prepared edible fats. Using DRCA, Indonesia’s most significant exports in the rising star category are natural rubber and its derivatives; cars and other motorized vehicles; fatty acids and their derivatives; lignite; unforged lead; ferroalloys; wires and cables; refined copper; petroleum and minerals; and margarine and its derivatives. These products showed positive growth higher than the global average, which means Indonesia is competitive in exporting these products. Thus, the government could prioritize these products for export.

Data Collection Improvement: Daily Self-Enumeration Accommodation Survey

Until now, BPS - Statistics Indonesia has conducted monthly accommodation surveys both for the star and non-star accommodation categories to provide information on commercial accommodation activities at the national and regional levels. Both star and non-star accommodation categories are done by complete enumeration in each region. Statistics include guest night and room capacity to obtain the occupancy rate of a hotel room. The data contains daily accommodation information that is collected every month, so then it will be entered completely in each region following the observation month. Due to the timeliness requirements for monthly press releases, BPS has implemented online data entry since 2017. It may seem obvious, regions that have more interest will have an impact on a bigger number of accommodations, which also affects the number of enumerators and may lead to such problems especially in response burden. Unfortunately, the same problem is also not easily avoided by regions with less accommodation, mostly due to the distance issues to the accommodation area and its spread in the region. Therefore, a new data collection strategy is required to provide respondents with convenience in order to increase response rates, as well as to reduce the workload of enumerators which also leads to the lower cost. The outbreak of COVID-19 has posed unprecedented problems for National Statistical Offices (NSOs) around the world, including BPS – Statistics Indonesia. This crisis has led us to think in new ways and make decisions that will change our statistical operations in order to meet ongoing data needs even throughout the epidemic. The purpose of this paper is to discuss the evolution of accommodation surveys, which are designed to not only solve problems but also achieve objectives. Currently, there are nearly 180 active users of this self-enumeration accommodation survey for about 142 distinct accommodations across Indonesia. Moreover, this addition has proven to have succeeded in increasing the response rate average from 57.17% in 2020 to 68,35% in 2021.

Penerapan Sistem Menu Engineering Dalam Upaya Peningkatan Kualitas Menu di Restoran Bintan Inti Executive Village Clubhouse

This research is a form of analysis and evaluation of the menu at the Bintan Inti Executive Village (BIEV) Clubhouse through a menu engineering system with the aim of improving the quality and effectiveness of the menu served. The formulation of the problem which is the basis of this research is how to improve the quality of the food and beverage menu through the menu engineering system and what recommendation actions should be taken based on the resulting data from the analysis that appears. This study uses variables, which are menu analysis in improving the quality of the menu at BIEV Clubhouse with sub variables, such as food cost, menu mix, and contribution margin. The results of this study that there were 8 menus or 30.77% menus with star categories, 5 menus or 19.23% menus with the plowhorse category, 4 menus or 15.38% menus with the puzzle category, and 9 menus or 34.62%. menu with dog category. The recommended follow-up actions to BIEV Clubhouse management is reducing the menu with the dog category, evaluating product prices and production costs for menus with the plowhorse category, taking suggestive selling steps for menus with the puzzle category, and maintaining the quality and performance of menus with the star category.

Customer participation in service innovation using SNS smartphone apps: an investigation of the Indian hotel service industry

PurposeExisting research lacks a comprehensive understanding of the individual factors that may transform an “ordinary” customer into an active participator in the service innovation process and/or the situational factors that determine a customer's participation in any stage of the service innovation process. The purpose of this paper is to fill these research gaps by developing and validating a conceptual framework on CPSIB in the Indian hotel industry by using smartphones to access SNS apps.Design/methodology/approachA cross-sectional survey design method was used in this study to collect representative samples with greater response rates. The target population included in this study were hotel guests of all of the star category hotels in New Delhi who had earlier experiences of staying in star category hotels. Structured questionnaire was formulated, which was later pre-tested to confirm its reliability and validity. Out of 400 questionnaires, 348 usable responses were obtained.FindingsThis research examines CPSIB in the Indian hotel industry using SNS smartphone apps. It confirms that user innovativeness and perceived trust in the service provider determine customers' participative service innovation behavior, which further results in positive adoption intention via SNS smartphone apps.Research limitations/implicationsThis research provides valuable insights into the hotel industry, specifically in the context of India. However, it has a few limitations that must be taken into account when generalizing its results.Practical implicationsFirst, investigating the key antecedents and consequences of CPSIB has important implications for marketing practitioners. Moreover, it was observed that hotel guests with higher innovativeness and trust in the service provider would show positive participative service innovation behavior toward innovating new services along with the hotel service providers, which may result in a positive adoption intention toward the newly developed services. Second, hoteliers should integrate hotel guests into hotel service innovation via the use of SNS smartphone apps.Social implicationsThis research conceptualizes that user innovativeness is a driving factor for CPSIB that may further generate a positive adoption intention toward newly developed services.Originality/valueTo the best of the authors’ knowledge, only a very few studies have tested the interrelationships between individual factors and customer participation behavior in the mobile technology-mediated service ecosystem simultaneously. Furthermore, research examining the individual and situational factors influencing CPSIB and adoption intention towards newly developed services using SNS smartphone apps is still in a nascent stage.

A Study on the Benefits of Sustainable Management Practices and its Association with Talent Retention in Star Category Hotels

Sustainable management encompasses ideas from sustainability and synthesizes them with the concepts of management. This paper focuses on studying the benefits related to sustainable management practices that are adopted and followed in the hotel industry with specific reference to Star Category Hotels of Pune Region and its association with retention of the talented employees in the organisation.The study had reviewed the practices adopted by star category hotels and its association with retaining the talented bunch of employees. The research design for these factors is then explained further, which is supported by a Chi-Square test as a tool of data interpretation. A structured questionnaire was circulated amongst the managerial level employees in star hotels of the Pune region and responses were collected. The study had revealed that employees do believe that parameters covered under the benefits of the talent retention are mutually beneficial for the organisation as well as the employees.

Convolutional neural networks for the detection of the early inspiral of a gravitational-wave signal

GW170817 has led to the first example of multi-messenger astronomy with observations from gravitational wave interferometers and electromagnetic telescopes combined to characterise the source. However, detections of the early inspiral phase by the gravitational wave detectors would allow the observation of the earlier stages of the merger in the electromagnetic band, improving multi-messenger astronomy and giving access to new information. In this paper, we introduce a new machine-learning-based approach to produce early-warning alerts for an inspiraling binary neutron star system, based only on the early inspiral part of the signal. We give a proof of concept to show the possibility to use a combination of small convolutional neural networks trained on the whitened detector strain in the time domain to detect and classify early inspirals. Each of those is targeting a specific range of chirp masses dividing the binary neutron star category into three sub-classes: light, intermediate and heavy. In this work, we focus on one LIGO detector at design sensitivity and generate noise from the design power spectral density. We show that within this setup it is possible to produce an early alert up to 100 seconds before the merger for the best-case scenario. We also present some future upgrades that will enhance the detection capabilities of our convolutional neural networks. Finally, we also show that the current number of detections for a realistic binary neutron star population is comparable to that of matched filtering and that there is a high probability to detect GW170817- and GW190425-like events at design sensitivity.

Determine competitiveness of Indonesian export commodities using static and dynamic revealed comparative analysis

The government continues to promote non-oil and gas exports because oil and gas exports have continued to decline since the decades of the 90s. Main commodity products are still dominated by primary products such as mining, agriculture and some low technology manufactured products. This results in low added value of the product. Indonesia needs products that are highly competitive in the international market. This article aims to analyze the level of competitiveness of Indonesian products in world trade. The analytical tool used is the static revealed comparative advantage (SRCA) and dynamic revealed comparative advantage (DRCA). The data used from the International Trade Centre are classified according to the Harmonized System (HS) from 2013 to 2019. The result is that by using SRCA, Indonesia has competitiveness for products: tin and articles group only contribute to the export value of 0.95% of Indonesia's total exports. The biggest share of exports is the group of mineral fuels, mineral oils, and products of their distillation; bituminous substances; minerals, group of goods Animal or vegetable fats and oils and their cleavage products; prepared edible fats; animal by 13.60%. In the DRCA, the largest export value is 10 groups included in the rising star category: natural rubber and its derivatives, cars and other motorized vehicles, fatty acids and their derivatives for industry, lignite, lead not forged, ferroalloys, wire, cable, and the like, refined copper, petroleum and mineral, and margarine and its derivatives. This indicates these products had positive growth, but growth in Indonesia was higher than the growth of similar products in the world.

SUSTAINABLE RECYCLING OF HOTEL WASTE WATER IN GOA

Goa, a tourist destination known for its alarming scenic beauty has seen a consistently rising trend in hotel occupancy for star category hotels. On an average a luxury hotel would consume approximately 200,000 litres of water per day. The waste water generated from this consumption is basically 30% of black water (sewage) and 70% of grey water (bath water, laundry waste water, etc). A study was carried out to harness the potential of grey water before dumping into water bodies per se. A membrane based bio reactor (MBR) designed for chemical and biological treatment of this waste water includes mechanisms like coagulation, flocculation & separation of the water ludge. The water is then validated for its BOD & COD levels as per the government norms and then membrane filtered to remove total dissolved solids (TDS). This filtered water is then subjected to biological treatment whereas the sludge is used in landfills. EM technology uses commercially available culture of microorganisms, comprising of Lactobacillus, photosynthetic bacteria and yeast for biological treatment of the waste water to render it safe for human use. Monitoring and water quality analysis revealed that microbial treatment considerably reduced the BOD. This innovative technology allows the recycling of waste water which can be made use of for different purposes like gardening, cleaning floors & hotel properties, washing of cars & flushing. Moreover, it requires low foot print and involves easy installation and less maintenance. Recycling of grey water would in turn curtail consumption, thus cutting cost for purchase of water and ensuring safety of consumers. In addition to MBR & EM Technology being economically feasible, safe and user-friendly, its usage is highly recommended to maintain a stable water table and preserve the integrity of the hospitality industry in Goa. It is surely an initiative to minimize water crisis thus maintaining a sustainable ecosystem.

Skin tear classification using machine learning from digital RGB image

AimSkin tears are traumatic wounds characterised by separation of the skin layers. Severity evaluation is important in the management of skin tears. To support the assessment and management of skin tears, this study aimed to develop an algorithm to estimate a category of the Skin Tear Audit Research classification system (STAR classification) using digital images via machine learning. This was achieved by introducing shape features representing complicated shape of the skin tears. MethodsA skin tear image was separated into small segments, and features of each segment were estimated. The segments were then classified into different classes by machine learning algorithms, namely support vector machine and random forest. Their performance in classifying wound segments and STAR categories was evaluated with 31 images using the leave-one-out cross validation. ResultsSupport vector machine showed an accuracy of 74% and 69% in classifying wound segments and STAR categories, respectively. The corresponding accuracy using random forest were 71% and 63%. ConclusionMachine learning algorithms revealed capable of classifying categories of skin tears. This could offer the potential to aid nurses in their management of skin tears, even if they are not specialised in wound care.

Organisational Agility and 7Ps of the Marketing Mix for the Post-COVID-19 Period: A Case Study of the Indian Informal Food Sector

This study uncovers the reality of the COVID-19 epidemic, acting as a significant hurdle for small restaurants' sustainability. The study used a purely qualitative methodology dealing with data collected from the industry to frame effective sustainability strategies to revamp the business. Hence, in-depth interviews to capture the real problems faced by restaurants were conducted. From the study, we understood that big cities such as Chennai, Bengaluru and Thiruvananthapuram took initiatives in the post-COVID-19 crisis to bring about changes in the business process, giving importance to online ordering and delivery, new cuisines and more hygienic transparency. Small cities such as Coimbatore, Thiruvalla and Kochi are still confident of running their businesses, but there may not be a drastic change in the process. However, their expectations of help from the government are high. Three major factors are being considered to be cornerstone elements, which are health, cleanliness and hygiene. In this research, the scope is limited only to restaurants in big and small cities, while large-sized star category hotels have not been considered.

Stress Management among the Employees in Hotel Industry: w.r.t. Rajamahendravaram

Hotel Industry is one of those industries that demand a lot of hard work, attention, presence of mind, right job attitude, multitasking and multi-processing skills. The level of employees can be classified into three categories, top, middle, and lower level. At all the three tiers of Employee levels, hotel industry is a demanding, and challenging area. However the designation name can vary according to the organization. The human resource in the star category hotels of Rajamahendravaram serve in different departments of the hotel. The jobs demand high skills, hard work, service attitude, competencies and commitment that cater to the needs of hospitality. The Human resource is bound to undergo stress of different types. Work stress places a very high toll on both employees and employers. The ever changing demands of the working world can increase levels of stress, especially for those who are consistently working under pressure. Whilst pressure has its positive side in raising performance, if such pressure becomes excessive it can lead to stress which has negative consequences. This paper throws light on significance of stress in hotel Industry, effect of stress on Performance, attitude and motivation of employees along with a hypothetical study on mobility of employees due to stress.

Categorization of business subjects: modern approaches and trends in the world and in Ukraine

The study focuses on the relevance of categorization in the management of the quality of service of hotel enterprises. The main approaches to categorization of hotel business actors in the world and in Ukraine have been analyzed, attention has been paid to the need to define key concepts in the management of the quality of the placement service, the issues of standards and the current categorization process in Ukraine, the direction of their solution has been substantiated. The spatial organization of categorized hotel enterprises in Ukraine was analyzed, and the dependence of the share with the rating and structure of the star categories on the tourist attractiveness of the regions was determined. The international and Ukrainian hotel corporations, whose enterprises are all categorized in a high segment, have a significant influence on the categorization. Among the main issues of categorization in Ukraine are as follows: obsolete, not appropriate current requirements regarding the quality of the service of regulations, complicated procedure of categorization, absence of a legal mechanism of influence on hotel enterprises, which publicly declare a certain category without passing the categorization process, unequal regulatory requirements for the passage of categorization the subjects of the hotel business of different legal form, capacity, historical status of the building, not formed in the majority of investors, top management, hotel business, professional consciousness that needs to be taken globally. Key words: hotel business subjects, categorization, certification, classification, standards, quality of service, categorization systems, normative-legal support.

A snapshot of solid waste generation in the hospitality industry. The case of a five-star hotel on the island of Malta

The history of tourism in Malta goes back 60 years. While widely hailed for its economic contribution, very little reference is made to the waste externalities that riddle the industry. In islands like Malta, the impacts of waste generation are more pronounced particularly due to the size of the country and its population density. Furthermore, waste originating from the hospitality establishments is, in its majority, landfilled.Five-star hotels have been established to generate more waste than hotels in lower star categories. Focusing on an established five-star hotel, this research provides a comprehensive case-study that utilises a mixed methodology approach which supplies quantitative figures of waste generated in the a-la-carte, buffet restaurants and residents’ rooms, together with qualitative methods to furnish information and insights about waste generation and reduction initiatives.Results point to the pervasive problem of plastic and single-use items. In one week, 692.5 kg of waste is generated in the residents’ rooms, 50.3 per cent of which consists of plastic. The impact of single-use items is exposed by the difference in the ‘other’ fraction which reaches 0.05 kg/person, a stark contrast to the remaining fractions which reach 0.01 kg/person.Food waste is an aspect of the hospitality industry that cannot be side-lined. Plate-waste, measured in a month-long audit performed at the a-la-carte restaurant, reaches an average of 0.21 and 0.16 kg/person at lunch and dinner respectively. The buffet dinner exposes greater wastage with 0.48 kg/person. Preparation waste reached 0.08 kg/person. The relationship between portion sizes and food waste is exposed when the removal of a side plate decreases waste generation from 0.059 kg/person to 0.043 kg/person.

Variable star classification using multiview metric learning

ABSTRACTComprehensive observations of variable stars can include time domain photometry in a multitude of filters, spectroscopy, estimates of colour (e.g. U-B), etc. When the objective is to classify variable stars, traditional machine learning techniques distill these various representations (or views) into a single feature vector and attempt to discriminate among desired categories. In this work, we propose an alternative approach that inherently leverages multiple views of the same variable star. Our multiview metric learning framework enables robust characterization of star categories by directly learning to discriminate in a multifaceted feature space, thus, eliminating the need to combine feature representations prior to fitting the machine learning model. We also demonstrate how to extend standard multiview learning, which employs multiple vectorized views, to the matrix-variate case which allows very novel variable star signature representations. The performance of our proposed methods is evaluated on the UCR Starlight and LINEAR data sets. Both the vector and matrix-variate versions of our multiview learning framework perform favourably – demonstrating the ability to discriminate variable star categories.

Impact of online reviews on hotel booking intention: The moderating role of brand image, star category, and price

This paper analyses the impact of online reviews on hotel booking intention. The moderating effect of brand image, star category, and price on this relationship was also tested. A quantitative approach has been followed by collecting questionnaires from a convenience sample of 432 customers who have previous experience with online booking. Results of the research revealed that reviews with positive valence do not affect booking intention, while reviews with negative valence have a strong impact. In addition, it was found that several moderators made this impact more or less severe. Brand image demonstrated a slight moderating effect due to the factor's inherent subjective nature. A moderating effect was also observed for both price importance and star category on the relationship. In conclusion, this study emphasizes the need for hotel managers to address online customer reviews, and specifically negative ones, to take advantage of promotional opportunities.

Dependency of Spanish Urban Hotels on Booking.Com

There is an increasing dependency of hotels on online travel agencies (OTAs) around the world, particularly in Booking.com when we focus on Europe, but there is a lack of information about accurate data related to market share of OTAs. Moreover, it is not possible to access individual information about hotels' dependency on OTAs because it is confidential. An indicator, based on the number of reviews of each hotel on Booking.com (RpR), is proposed as a proxy for hotel reservations. It does not provide the exact number of reservations made through Booking.com, but allows comparing dependency levels. Results from Spanish urban hotels suggest higher dependency percentage than in previous research using surveys at a European level. Independent hotels and hotels with small size or low star category are clearly more dependent on Booking.com. The RpR could be used as a benchmarking tool for hotels when comparing with competitors and can also function as an indicator of the evolution of the dependence on OTAs for individual hotels. The methodology described can be applied to other OTAs that have a similar reviewing system, like Expedia, Agoda or HRS, which would provide estimations about competitors' distribution mix.

Long-term stellar variability in the Galactic Centre region

We report the detection of variable stars within a 11.5' x 11.5' region near the Galactic centre (GC) that includes the Arches and Quintuplet clusters, as revealed by the VISTA Variables in the Via Lactea (VVV) survey. There are 353 sources that show Ks-band variability, of which the large majority (81%) correspond to red giant stars, mostly in the asymptotic giant branch (AGB) phase. We analyze a population of 52 red giants with long-term trends that cannot be classified into the typical pulsating star categories. Distances and extinctions are calculated for 9 Mira variables, and we discuss the impact of the chosen extinction law on the derived distances. We also report the presence of 48 new identified young stellar object (YSO) candidates in the region.